A quasi-experimental assessment of the effectiveness of the Community Health Strategy on health outcomes in Kenya
Bibliographic record
Abstract
Despite focused health policies and reform agenda, Kenya has challenges in improving households’ situation in poverty and ill health; interventions to address the Millennium Development Goals in maternal and child health, such as focused antenatal care and immunization of children, are yet to achieve success. Research has shown that addressing the demand side is critical in improving health outcomes. This paper presents a model for health systems performance improvement using a strategy that bridges the interface between the community and the health system. The study employed quasi-experimental design, using pre- and post-intervention surveys in intervention and control sites. The intervention was the implementation of all components of the Kenyan Community Health Strategy, guided by policy. The two year intervention (2011 and 2012) saw the strategy introduced to selected district health management teams, service providers, and communities through a series of three-day training workshops that were held three times during the intervention period. Baseline and endline surveys were conducted in intervention and control sites where community unit assessment was undertaken to determine the status of health service utilization before and after the intervention. A community health unit consists of 1000 households, a population of about 5000, served by trained community health workers, each supporting about 20 to 50 households. Data was organized and analyzed using Excel, SPSS, Epi info, Stata Cal, and SAS. A number of health indicators, such as health facility delivery, antenatal care, water treatment, latrine use, and insecticide treated nets, improved in the intervention sites compared to non-interventions sites. The difference between intervention and control sites was statistically significant (p<0.0001) for antenatal care, health facility delivery, water treatment, latrine use, use of insecticide treated nets, presence of clinic card, and measles vaccination. Degree of improvement across the various indicators measured differed by socio-demographic contexts. The changes were greatest in the rural agrarian sites, compared to peri-urban and nomadic sites. The study showed that most of the components of the strategy were implemented and sustained in different socio-demographic contexts, while participatory community planning based on household information drives improvement of health indicators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".